• Journal of Environmental Impact Assessment
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• v.8 no.4
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• pp.73-79
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• 1999

This study was conducted as a preliminary study for the mitigation of acid rain which has been a serious environmental problem in both regional and global scales. In this study, sulfur dioxide emission was estimated at city and gun(county) level. Also, this study represents the estimated sulfur dioxide emission with using a geographical information system which includes administrative boundaries. The results of this study are expected to serve as a sulfur dioxide emission mitigation policy guidance and a basis of a future emission model and a comprehensive global warming model. Moreover, thanks to the geographical information system, the results are also expected to help carrying out clear policy goals and setting up sulfur dioxide emission mitigation measures in regional environmental planning processes, which currently have been implemented in some cities and counties in Korea.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.1-20
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• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.

• Journal of Korean Society for Atmospheric Environment
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• v.9 no.1
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• pp.69-77
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• 1993

Exhaust emissions are calculated as a product of the emission factor and the vehicle kilometer traveled(VKT). The emission factor is a function of several parameters such as vehicle model year, vehicle mileage, traffic conditions, etc. The representative driving cycles classified as ten different types of an average vehicle speed were selected by analyzing passenger car driving patterns in Seoul. 51 vehicles were sampled and analyzed by types of vehicles, fuels used, model years and vehicle mileages also, exhaust emissions of them were measured by chassis dynamometer. Regression equations between average vehicle speeds and exhaust emissions are made for the estimation of emission factors at different vehicle speeds. Annual emission rates of air pollutants from motor vehicles in Korea were 1116$\times10^3 ton, 149\times10^3 ton, 413\times10^3 ton and 67\times10^3$ ton for CO, HC, NOx and particulats, respetively in 1990. It was found that 56% of CO and 49% of HC were originated from passenger cars and taxis, in addition, 87% of NOx and 100% of particulates were from buses and trucks using diesel fuels.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.1
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• pp.69-76
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• 2010

While increased use of motor cycles in the recent years for various demands could worsen air quality, only few studies have been conducted on estimation of emission factors and characterization of emissions from motorcycle. In this study, emissions from selected six models of motorcycle based on largest market share and production rate were investigated. To investigate gaseous and carbonaceous air pollutants, such as carbon monoxide (CO), total hydrocarbon (THC), nitrogen oxide ($NO_x$), elemental carbon (EC) and organic carbon (OC), total 124 motorcycles between 2003 and 2007 model year were tested with regulatory driving conditions, such as CVS-40 and CVS-47 mode. These motorcycles were further sub-categorized based on their displacement (< 50 cc, 50~150 cc, and $\geq$ 150 cc), type of stroke (2- and 4 strokes) and model year (2003~2005 and 2006~2007). Tested motorcycles with recent model year (2006~2007) exhibited less emissions of regulatory gaseous and carbonaceous air pollutants compared to old model year (2003~2005). Chemical analysis showed that CO present in highest concentration followed by THC and $NO_x$ for all tested motorcycles. Interestingly, two strokes motorcycle produced higher THC emission but less CO and $NO_x$ than those of four strokes. For all types of displacement and stroke, emission factors (gram per kilometer) of THC and CO except $NO_x$ with recent model year (2006~2007) showed decreased trend compared to old model year (2003~2005). In addition to this, due to mixed combustion between gasoline fuel and lubricant, two strokes motorcycle showed OC > EC emission trend.

• Proceedings of the KIPE Conference
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• 2009.11a
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• pp.117-119
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• 2009

This paper presents a simulation model based on support vector regression (SVR) for flicker emission estimation from wind turbines. Training patterns are developed by varying the wind speed and network parameters that might affect the expected flicker levels. A comparison is done to the fixed speed wind turbine (WT), which leads to a conclusion that the factors mentioned above have different influences on flicker emission. The simulation results have shown that the flicker estimation is performed accurately.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2005.11a
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• pp.437-439
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• 2005

• Journal of Environmental Impact Assessment
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• v.14 no.4
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• pp.227-235
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• 2005

Source contribution for VOCs collected in Seoul metropolitan area was conducted using PAMs (Photochemical assessment monitoring system) data and CMB(Chemical Mass Balance) model8.0, in order to estimate spatial and temporal variations of VOCs source contribution in that area, and also to compare with corresponding emission inventory. VOCs data used in model calculation were collected at 6 different sites of PAMs(Seokmori, Guwoldong, Simgokdong, Bulgwangdong, Jeongdong and Yangpyeong) and 22 out of 56 VOCs species were analyzed from June 2002 to march 2003 and used for CMB model estimation. The result showed that vehicle exhaust, coating and energy combustion were important sources of VOCs in Seoul metropolitan area, averaging 32.6%, 25.5% and 25.1%, respectively. In this study as well as other references, it was revealed that vehicle exhaust is the main contributor of urban area VOCs, but there is remarkable contrast between emission inventory and model estimation. Vehicle exhaust portion is seriously underestimated while coating is usually overestimated in emission estimates, compared to CMB results. Therefore, it is considered to assert and confirm the uncertainty of emission estimates and clarify the distinction between two other source apportionment methods.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.4
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• pp.25-33
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• 2014

As global warming becoming an environmentally serious issue, more attention is drawn to fuel consumption which is the direct source of green house gas emission. The fuel consumption by aircraft operation is not an exception. Motivated by the societal and environmental context, this paper explains a method for estimation of aircraft fuel consumed during their flights as well as the computational process using real flight track data. Applying so-called 'Total Energy Model' along with aircraft specific parameters provided in EUROCONTROL's Base of Aircraft Data (BADA) to aircraft radar track data, we estimate fuel consumption of individual aircraft flown between Gimpo and Jeju airports. We then assess the estimation accuracy by comparing the estimated fuel consumption with the actual one collected from an airline. The computational results are quite encouraging in that the method is able to estimate the actual fuel consumption within ${\pm}6{\sim}11%$ of error margin. The limitations and possible enhancements of the method are also discussed.

• Journal of Environmental Impact Assessment
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• v.21 no.3
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• pp.409-415
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• 2012

Post-kyoto regime has been discussing with the GHG reduction commitment. GHG energy target management system also has been applied for the domestic measures in the country. Universities are major emission sources for GHG. It is very important for campus to built the GHG inventory system and estimate the potential GHG emission reduction. In general, GHG inventory on the campus was taken by the IPCC guidance with the classification of scope 1, 2, and 3. Electricity was the highest portion of GHG emission on the campus as 5,053.90 $tonsCO_2eq/yr$ in 2009. Manufacturing sector was the second high emission and meant GHG in laboratory. Potential GHG reduction was planned by several assumptions such as installation of occupancy sensor, exchanging LED lamp and photovoltaic power generation. These reduction scenarios was simulated by LEAP model. In 2020, outlook of GHG emission was estimated by 17,435.98 tons of $CO_2$ without any plans of reduction. If the reduction scenarios was applied in 2020, GHG emission would be 16,507.60 tons of $CO_2$ as 5.3% potential reduction.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.2
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• pp.123-135
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• 1997

An air pollutant emission inventory system for the input preparations of photochemical dispersion model was developed. Using the system, anthropogenic emissions as well as biogenic emissions in the Seoul metropolitan area were calculated. Anthropogenic emission by fuel combustion using regional cosumption data, and the laundries and so forth was estimated. The biogenic emission was estimated based upon meteorological data and the distribution of land use type in the study area. The anthropogenic emission of pollutants was highest in Seoul, and the second highest in Inchon. TSP and $SO_2$ were found large quantities during the winter due to increased consumption of heating oil. NOx and THC were emitted without seasonal variation. Among biogenic emissions, PAR was very common while NO was the least common. PAR, OLE, and ALD2 were emitted in large volumes in coniferous forest areas, while ISOP was emitted in deciduous forest areas. Generally, most biogenic emissions increased during daytime, and peaked between oen and two o'clock. Because of strong solar radiation, emission during the summer was high. Biogenic NO emissions were found to be lower compared to anthropogenic emissons, and other VOC was indicated relatively high. In the study area, among biogenic emissions PAR was found to be 3 times, OLE 8 times,and ALD2 12 times more common than among anthropogenic emissions.